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AI and ML are revolutionizing electronic system design, optimization, and security, fueling innovations in avionics, electrification, industrial automation, and healthcare. However, traditional electronics struggle with AI’s growing computational complexity, lacking real-time adaptability, energy efficiency, and resilience.

This research directly addresses these challenges by developing high-performance, secure, and adaptive AI-driven architectures. With increasing global investments in AI-powered embedded systems, neuromorphic computing, and reconfigurable hardware, this project enables researchers to push the boundaries of AI-integrated electronics, shaping the future of autonomous and mission-critical intelligent systems

This MSc by Research project explores the integration of AI and ML into advanced electronic systems, focusing on two key areas: embedding AI into electronic hardware and enhancing electronic performance and resilience using AI techniques. The research aims to develop intelligent, adaptive, and high-performance electronic architectures that support real-time processing, energy efficiency, and security in mission-critical applications. Students will have the flexibility to specialize in areas such as (not limited to):

AI-Integrated Electronics for Next-Generation Embedded Systems

1- Neuromorphic and AI-Optimized Processors – Design AI-specific chip architectures, including neuromorphic and domain-specific accelerators (TPUs, NPUs, FPGAs), for low-power and real-time AI processing.

2- AI-Driven Hardware Security and Embedded Resilience – Explore AI-powered hardware security primitives, anomaly detection, and self-healing mechanisms for IoT, cyber-physical systems, and mission-critical applications.

3- Reconfigurable AI-Embedded Systems – Develop adaptive FPGA/ASIC architectures that dynamically reconfigure based on AI workloads, optimising performance, energy efficiency, and functionality.

AI for High-Performance Computing and Future Data Centres

1- AI-Optimized Electronics for Edge and Cloud AI Acceleration – Investigate AI-enhanced data centre electronics, optimizing workload distribution, energy efficiency, and cooling for scalable AI computing.

2- AI-Assisted Electronic Circuit Design and Optimization – Apply ML techniques for automated circuit design, fault detection, and performance scaling in AI-driven computing infrastructures.

3- Photonics and AI Co-Optimization for High-Speed Computing – Explore AI-optimized photonics and THz interconnects for ultra-fast, low-power data transmission in cloud and AI processors.

AI-Powered Electronics for Aviation, Electrification, and Autonomous Systems

1- AI for Smart Avionics and Electrification – Develop AI-integrated power systems, flight control electronics, and autonomous avionics for hybrid-electric and more-electric aircraft.

2- AI-Enhanced Power Electronics for Electrified Transport – Optimize power converters, battery management, and energy efficiency in electric aircraft, vehicles, and smart mobility systems.

3- AI-Assisted Radar, Sensing, and Navigation Electronics – Improve THz sensing, radar processing, and autonomous navigation with AI-enhanced electronic components.

AI for Semiconductor Design, Manufacturing, and Electronic Packaging

1- AI-Optimized Semiconductor Fabrication and Packaging – Use AI for defect detection, process optimization, and advanced materials engineering in semiconductor and metamaterial-based packaging.

2- Self-Healing and AI-Enhanced Electronics – Develop AI-powered self-repairing and self-optimizing electronic components that enhance longevity and resilience.

3- AI-Driven RF, Photonic, and THz Electronics Design – Leverage AI for optimizing metamaterials and advanced electronic circuits for next-gen wireless and optical communication.

Cranfield is a unique learning environment with world-class programmes, unrivalled facilities, and close industry links, attracting top students and experts globally. As an internationally recognized leader in AI, embedded system design, and intelligent systems research, Cranfield fosters innovation through applied research, bridging academia and industry. Students will have access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research.

This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established with Boeing, Rolls-Royce, BAE Systems, Meggitt, and Thales. IVHM is part of DARTeC, advancing research in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC), Airbus, and Rolls-Royce, students gain industry exposure and further research opportunities.

Additionally, IVHM hosts Seretonix, a research group specialising in secure electronic design, AI-driven system resilience, and intelligent hardware security. Through EUROPRACTICE partnership, IVHM provides access to advanced CAD tools, IC prototyping, and technical training, equipping students with cutting-edge skills.

This self-funded MSc by Research allows students to tailor their projects to industry trends, working alongside leading experts in AI-integrated electronics to contribute to next-generation intelligent systems.

This research will advance AI-integrated electronic systems, creating intelligent, efficient, and resilient next-generation hardware. By embedding AI into electronic architectures and leveraging AI-driven optimisation, the project will enable real-time adaptability, enhanced security, and energy-efficient processing in mission-critical applications. The expected outcomes include neuromorphic AI processors, reconfigurable FPGA/ASIC-based AI accelerators, and AI-driven fault-tolerant embedded systems (all depends on the chosen project based on the applicant's interests).

The project’s AI-enhanced solutions will set new benchmarks for intelligent electronics across aviation, electrification, smart mobility, cybersecurity, and industrial automation. Research advancements in self-healing electronics, predictive maintenance, and AI-powered system resilience will extend hardware reliability, optimize performance, and reduce failure risks in complex electronic systems. With increasing global investments in AI-optimized semiconductors, embedded intelligence, and secure AI-electronic integration, this research will position students at the forefront of AI-driven innovation, equipping them with the expertise to shape the future of high-performance, adaptive, and autonomous electronics.

This MSc by Research offers a structured, industry-focused, and publication-driven research experience. The project follows a unique phase-based approach, where each stage—study, research execution, experimentation, analysis and reporting—results in a publishable paper. This ensures that students graduate with a strong academic profile, ready for impactful careers in both research and industry.

Students will engage directly with industries, e.g., Boeing, Thales, Airbus, and BAE Systems, presenting their research in technical reviews. They will also have opportunities to publish and present at top-tier IEEE and AI-electronics conferences, gaining international recognition. Training in FPGA/ASIC computing, and AI-embedded electronics will be supported through Cranfield’s EUROPRACTICE partnership and industry collaborations.

Beyond research, this MSc provides global networking opportunities, with potential for international collaborations with leading AI-electronics research institutions. The combination of academic excellence, industry exposure, and hands-on training ensures that students develop a unique skill set, preparing them for leadership roles in AI-driven semiconductor design, embedded AI systems, cybersecurity, and aerospace technology.

Graduates of this MSc by Research will emerge as specialists in AI-integrated electronics, equipped with the skills to drive innovation in AI-powered hardware, embedded security, and intelligent automation. Through structured research phases, hands-on experimentation, and direct collaboration with industry leaders, students will gain expertise in AI-driven fault detection, self-healing electronics, and advanced system optimisation.

This research experience significantly enhances employability, preparing graduates for high-impact careers in AI-driven semiconductor design, intelligent automation, and next-generation secure computing. With rising industry demand for AI-electronics expertise, graduates will be well-positioned for roles in cutting-edge research, technology development, and industrial applications across multiple sectors.